code: def test_train_unconditional(self):
      with tempfile.TemporaryDirectory() as tmpdir:
          test_args = f"""
                  examples/unconditional_image_generation/train_unconditional.py
                  --dataset_name hf-internal-testing/dummy_image_class_data
                  --model_config_name_or_path diffusers/ddpm_dummy
                  --resolution 64
                  --output_dir {tmpdir}
                  --train_batch_size 2
                  --num_epochs 1
                  --gradient_accumulation_steps 1
                  --ddpm_num_inference_steps 2
                  --learning_rate 1e-3
                  --lr_warmup_steps 5
                  """.split()
  
          run_command(self._launch_args + test_args, return_stdout=True)
          # save_pretrained smoke test
          self.assertTrue(
              os.path.isfile(
                  os.path.join(
                      tmpdir,
                      "unet",
                      "diffusion_pytorch_model.safetensors",
                  )
              )
          )
          self.assertTrue(
              os.path.isfile(
                  os.path.join(
                      tmpdir, "scheduler", "scheduler_config.json"
                  )
              )
          )
  
file_path: diffusers/examples/unconditional_image_generation/test_unconditional.py
imports: import logging
  import os
  import sys
  import tempfile
  from test_examples_utils import ExamplesTestsAccelerate, run_command
label_desc: Use image node_id 1 for calling the Unconditional obj's underlying member method code with example usage: obj.test_train_unconditional() without return types